WSA Browser

Glossary of WSA attributes

This Glossary alphabetically lists all attributes used in the UKIDSSDR6 database(s) held in the WSA. If you would like to have more information about the schema tables please use the UKIDSSDR6 Schema Browser (other Browser versions).

A B C D E F G H I J K L M
N O P Q R S T U V W X Y Z

N

Name Schema Table Database Description Type Length Unit Default Value Unified Content Descriptor

N1 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 1 int 4 -9

N2 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 2 int 4 -9

N3 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 3 int 4 -9

N3_6 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 3.6um IRAC (Band 1) int 4 -9

N4 glimpse_hrc_inter, glimpse_mca_inter GLIMPSE Possible number of detections for band 4 int 4 -9

N4_5 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 4.5um IRAC (Band 2) int 4 -9

N5_8 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 5.8um IRAC (Band 3) int 4 -9

N8_0 glimpse1_hrc, glimpse1_mca, glimpse2_hrc, glimpse2_mca GLIMPSE Number of possible detections for 8.0um IRAC (Band 4) int 4 -9

n_blank twomass_xsc 2MASS number of blanked source records. smallint 2 NUMBER

N_DETECTIONS twoxmm XMM The number of detections of the unique source SRCID used to derive the averaged values. int 4

n_ext twomass_scn 2MASS Number of regular extended sources detected in scan. int 4 NUMBER

N_SPEC mgcBrightSpec MGC Total number of spectra for this object smallint 2

n_sub twomass_xsc 2MASS number of subtracted source records. smallint 2 NUMBER

name Filter WSA The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16 NOTE

name Filter WSACalib The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16 NOTE

name Filter WSATransit The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16 NOTE

name RequiredMosaic WSA Name of the mosaiced product varchar 64 ??

name RequiredMosaic WSACalib Name of the mosaiced product varchar 64 ??

name RequiredMosaic WSATransit Name of the mosaiced product varchar 64 ??

name RequiredStack WSA Name of the stacked product varchar 64 ??

name RequiredStack WSACalib Name of the stacked product varchar 64 ??

name RequiredStack WSATransit Name of the stacked product varchar 64 ??

name Survey WSA The short name for the survey varchar 128 ??

name Survey WSACalib The short name for the survey varchar 128 ??

name Survey WSATransit The short name for the survey varchar 128 ??

name iras_asc, iras_psc IRAS Source Name varchar 11 ID_MAIN

name ukirtFSstars WSA reference name of field varchar 16 NONE ????

name ukirtFSstars WSACalib reference name of field varchar 16 NONE ????

nbjAperMag1 calSynopticSource WSACalib Extended source Nbj aperture corrected mag (1.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag1Err calSynopticSource WSACalib Error in extended source Nbj mag (1.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag2 calSynopticSource WSACalib Extended source Nbj aperture corrected mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag2Err calSynopticSource WSACalib Error in extended source Nbj mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag3 calSource WSACalib Default point/extended source Nbj aperture corrected mag (2.0 arcsec aperture diameter)
If in doubt use this flux estimator real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag3 calSynopticSource WSACalib Default point/extended source Nbj aperture corrected mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag3Err calSource, calSynopticSource WSACalib Error in default point/extended source Nbj mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag4 calSource, calSynopticSource WSACalib Extended source Nbj aperture corrected mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag4Err calSource, calSynopticSource WSACalib Error in extended source Nbj mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag5 calSynopticSource WSACalib Extended source Nbj aperture corrected mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag5Err calSynopticSource WSACalib Error in extended source Nbj mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag6 calSource WSACalib Extended source Nbj aperture corrected mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag6Err calSource WSACalib Error in extended source Nbj mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjaStratAst calVarFrameSetInfo WSACalib Strateva parameter, a, in fit to astrometric rms vs magnitude in Nbj band, see Sesar et al. 2007. real 4 -0.9999995e9

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated.

nbjaStratPht calVarFrameSetInfo WSACalib Strateva parameter, a, in fit to photmetric rms vs magnitude in Nbj band, see Sesar et al. 2007. real 4 -0.9999995e9

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjbestAper calVariability WSACalib Best aperture (1-6) for photometric statistics in the Nbj band int 4 -9999

Aperture magnitude (1-6) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449)

nbjbStratAst calVarFrameSetInfo WSACalib Strateva parameter, b, in fit to astrometric rms vs magnitude in Nbj band, see Sesar et al. 2007. real 4 -0.9999995e9

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated.

nbjbStratPht calVarFrameSetInfo WSACalib Strateva parameter, b, in fit to photometric rms vs magnitude in Nbj band, see Sesar et al. 2007. real 4 -0.9999995e9

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjchiSqAst calVarFrameSetInfo WSACalib Goodness of fit of Strateva function to astrometric data in Nbj band real 4 -0.9999995e9

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated.

nbjchiSqpd calVariability WSACalib Chi square (per degree of freedom) fit to data (mean and expected rms) real 4 -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjchiSqPht calVarFrameSetInfo WSACalib Goodness of fit of Strateva function to photometric data in Nbj band real 4 -0.9999995e9

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjClass calSource, calSourceRemeasurement, calSynopticSource WSACalib discrete image classification flag in Nbj smallint 2 -9999 CLASS_MISC

nbjClassStat calSource, calSourceRemeasurement, calSynopticSource WSACalib N(0,1) stellarness-of-profile statistic in Nbj real 4 -0.9999995e9 STAT_PROP

nbjcStratAst calVarFrameSetInfo WSACalib Strateva parameter, c, in fit to astrometric rms vs magnitude in Nbj band, see Sesar et al. 2007. real 4 -0.9999995e9

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated.

nbjcStratPht calVarFrameSetInfo WSACalib Strateva parameter, c, in fit to photometric rms vs magnitude in Nbj band, see Sesar et al. 2007. real 4 -0.9999995e9

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjDeblend calSource WSACalib placeholder flag indicating parent/child relation in Nbj int 4 -99999999 CODE_MISC

This CASU pipeline processing source extraction flag is a placeholder only, and is always set to zero in all passbands in the merged source lists. If you need to know when a particular image detection is a component of a deblend or not, test bit 4 of attribute ppErrBits (see corresponding glossary entry) which is set by WFAU's post-processing software based on testing the areal profiles aprof2-8 (these are set by CASU to -1 for deblended components, or positive values for non-deblended detections). We encode this in an information bit of ppErrBits for convenience when querying the merged source tables.

nbjDeblend calSourceRemeasurement, calSynopticSource WSACalib placeholder flag indicating parent/child relation in Nbj int 4 -99999999 CODE_MISC

nbjEll calSource, calSourceRemeasurement, calSynopticSource WSACalib 1-b/a, where a/b=semi-major/minor axes in Nbj real 4 -0.9999995e9 PHYS_ELLIPTICITY

nbjeNum calMergeLog, calSynopticMergeLog WSACalib the extension number of this Nbj frame tinyint 1 NUMBER

nbjErrBits calSource, calSynopticSource WSACalib processing warning/error bitwise flags in Nbj int 4 -99999999 CODE_MISC

Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture.

nbjErrBits calSourceRemeasurement WSACalib processing warning/error bitwise flags in Nbj int 4 -99999999 CODE_MISC

nbjEta calSource, calSynopticSource WSACalib Offset of Nbj detection from master position (+north/-south) real 4 arcsec -0.9999995e9 POS_EQ_DEC_OFF

When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the LAS, you might wish to insist that the offsets in the selected sample are all below 1 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want.

nbjexpML calVarFrameSetInfo WSACalib Expected magnitude limit of frameSet in this in Nbj band. real 4 -0.9999995e9

The expected magnitude limit of an intermediate stack, based on the total exposure time. expML=Filter.oneSecML+1.25*log10(totalExpTime). Since different intermediate stacks can have different exposure times, the totalExpTime is the minimum, as long as the number of stacks with this minimum make up 10% of the total. This is a more conservative treatment than just taking the mean or median total exposure time.

nbjExpRms calVariability WSACalib Rms calculated from polynomial fit to modal RMS as a function of magnitude in Nbj band real 4 mag -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjGausig calSource, calSourceRemeasurement, calSynopticSource WSACalib RMS of axes of ellipse fit in Nbj real 4 pixels -0.9999995e9 MORPH_PARAM

nbjHallMag calSource WSACalib Total point source Nbj mag real 4 mag -0.9999995e9 PHOT_MAG

nbjHallMagErr calSource WSACalib Error in total point source Nbj mag real 4 mag -0.9999995e9 ERROR

nbjIntRms calVariability WSACalib Intrinsic rms in Nbj-band real 4 mag -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjMag calSourceRemeasurement WSACalib Nbj mag (as appropriate for this merged source) real 4 mag -0.9999995e9 PHOT_MAG

nbjMagErr calSourceRemeasurement WSACalib Error in Nbj mag real 4 mag -0.9999995e9 ERROR

nbjMagMAD calVariability WSACalib Median Absolute Deviation of Nbj magnitude real 4 mag -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjMagRms calVariability WSACalib rms of Nbj magnitude real 4 mag -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmaxCadence calVariability WSACalib maximum gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjMaxMag calVariability WSACalib Maximum magnitude in Nbj band, of good detections real 4 -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmeanMag calVariability WSACalib Mean Nbj magnitude real 4 mag -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmedCadence calVariability WSACalib median gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjmedianMag calVariability WSACalib Median Nbj magnitude real 4 mag -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmfID calMergeLog, calSynopticMergeLog WSACalib the UID of the relevant Nbj multiframe bigint 8 ID_FRAME

nbjminCadence calVariability WSACalib minimum gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjMinMag calVariability WSACalib real 4 -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjndof calVariability WSACalib Number of degrees of freedom for chisquare int 4 -99999999

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjnDofAst calVarFrameSetInfo WSACalib Number of degrees of freedom of astrometric fit in Nbj band. smallint 2 -9999

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated.

nbjnDofPht calVarFrameSetInfo WSACalib Number of degrees of freedom of photometric fit in Nbj band. smallint 2 -9999

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the median-absolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjnFlaggedObs calVariability WSACalib Number of detections in Nbj band flagged as potentially spurious by calDetection.ppErrBits int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjnGoodObs calVariability WSACalib Number of good detections in Nbj band int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjNgt3sig calVariability WSACalib Number of good detections in Nbj-band that are more than 3 sigma deviations smallint 2 -9999

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjnMissingObs calVariability WSACalib Number of Nbj band frames that this object should have been detected on and was not int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjObjID calSource, calSourceRemeasurement, calSynopticSource WSACalib DEPRECATED (do not use) bigint 8 -99999999 ID_NUMBER

This attribute is included in source tables for historical reasons, but it's use is not recommended unless you really know what you are doing. In general, if you need to look up detection table attributes for a source in a given passband that are not in the source table, you should make an SQL join between source, mergelog and detection using the primary key attribute frameSetID and combination multiframeID, extNum, seqNum to associate related rows between the three tables. See the Q&A example SQL for more information.

nbjPA calSource, calSourceRemeasurement, calSynopticSource WSACalib ellipse fit celestial orientation in Nbj real 4 Degrees -0.9999995e9 POS_POS-ANG

nbjPetroMag calSource WSACalib Extended source Nbj mag (Petrosian) real 4 mag -0.9999995e9 PHOT_MAG

nbjPetroMagErr calSource WSACalib Error in extended source Nbj mag (Petrosian) real 4 mag -0.9999995e9 ERROR

nbjppErrBits calSource, calSynopticSource WSACalib additional WFAU post-processing error bits in Nbj int 4 0 CODE_MISC

Post-processing error quality bit flags assigned (NB: from UKIDSS DR2 release onwards) in the WSA curation procedure for survey data. From least to most significant byte in the 4-byte integer attribute byte 0 (bits 0 to 7) corresponds to information on generally innocuous conditions that are nonetheless potentially significant as regards the integrity of that detection; byte 1 (bits 8 to 15) corresponds to warnings; byte 2 (bits 16 to 23) corresponds to important warnings; and finally byte 3 (bits 24 to 31) corresponds to severe warnings:

Byte Bit Detection quality issue Threshold or bit mask Applies to

Decimal Hexadecimal

0 4 Deblended 16 0x00000010 LAS, GCS, GPS, DXS

0 6 Bad pixel(s) in default aperture 64 0x00000040 LAS, GCS, GPS, DXS

2 16 Close to saturated 65536 0x00010000 LAS, GCS, GPS

2 19 Possible crosstalk artefact/contamination 524288 0x00080000 LAS, GCS, DXS

2 22 Lies within a dither offset of the stacked frame boundary 4194304 0x00400000 LAS, GCS, GPS, DXS

In this way, the higher the error quality bit flag value, the more likely it is that the detection is spurious. The decimal threshold (column 4) gives the minimum value of the quality flag for a detection having the given condition (since other bits in the flag may be set also; the corresponding hexadecimal value, where each digit corresponds to 4 bits in the flag, can be easier to compute when writing SQL queries to test for a given condition). For example, to exclude all K band sources in the LAS having any error quality condition other than informational ones, include a predicate ... AND kppErrBits ≤ 255. See the SQL Cookbook and other online pages for further information.

nbjppErrBits calSourceRemeasurement WSACalib additional WFAU post-processing error bits in Nbj int 4 0 CODE_MISC

nbjprobVar calVariability WSACalib Probability of variable from chi-square (and other data) real 4 -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjPsfMag calSource WSACalib Point source profile-fitted Nbj mag real 4 mag -0.9999995e9 PHOT_MAG

nbjPsfMagErr calSource WSACalib Error in point source profile-fitted Nbj mag real 4 mag -0.9999995e9 ERROR

nbjSeqNum calSource, calSynopticSource WSACalib the running number of the Nbj detection int 4 -99999999 ID_NUMBER

nbjSeqNum calSourceRemeasurement WSACalib the running number of the Nbj remeasurement int 4 -99999999 ID_NUMBER

nbjSerMag2D calSource WSACalib Extended source Nbj mag (profile-fitted) real 4 mag -0.9999995e9 PHOT_MAG

nbjSerMag2DErr calSource WSACalib Error in extended source Nbj mag (profile-fitted) real 4 mag -0.9999995e9 ERROR

nbjskewness calVariability WSACalib Skewness in Nbj band (see Sesar et al. 2007) real 4 -0.9999995e9

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjtotalPeriod calVariability WSACalib total period of observations (last obs-first obs) real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjVarClass calVariability WSACalib Classification of variability in this band smallint 2 -9999

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjXi calSource, calSynopticSource WSACalib Offset of Nbj detection from master position (+east/-west) real 4 arcsec -0.9999995e9 POS_EQ_RA_OFF

When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the LAS, you might wish to insist that the offsets in the selected sample are all below 1 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want.

nBlockSize RequiredMosaic WSACalib CASU/SEX source extraction tool option to override the default background blockdown size (=64, the recommended value) smallint 2 pixels -9999 ??

nBlockSize RequiredMosaic WSATransit CASU/SEX source extraction tool option to override the default background blockdown size (=64, the recommended value) smallint 2 pixels -9999 ??

nBlockSize RequiredMosaic, RequiredStack WSA CASU/SEX source extraction tool option to override the default background blockdown size (=64, the recommended value) smallint 2 pixels -9999 ??

ndet twomass_psc 2MASS Frame detection statistics. varchar 6 NUMBER

NED_CLASS mgcBrightSpec MGC MGC translation of NED_IDENT smallint 2

NED_DEC mgcBrightSpec MGC NED object declination in deg (J2000) float 8

NED_IDENT mgcBrightSpec MGC NED identification varchar 4

NED_N mgcBrightSpec MGC Number of NED objects matched to this MGC object smallint 2

NED_NAME mgcBrightSpec MGC NED object name varchar 32

NED_RA mgcBrightSpec MGC NED object right ascension in deg (J2000) float 8

NED_ZHELIO mgcBrightSpec MGC NED heliocentric redshift real 4

NED_ZQUAL mgcBrightSpec MGC NED redshift quality tinyint 1

neighboursSchema Programme WSA Script file that describes the neighbour tables schema for this programme varchar 64 ??

neighboursSchema Programme WSACalib Script file that describes the neighbour tables schema for this programme varchar 64 ??

neighboursSchema Programme WSATransit Script file that describes the neighbour tables schema for this programme varchar 64 ??

neighbourTable RequiredNeighbours WSA the name of the neighbour join table varchar 256 ID_TABLE

neighbourTable RequiredNeighbours WSACalib the name of the neighbour join table varchar 256 ID_TABLE

neighbourTable RequiredNeighbours WSATransit the name of the neighbour join table varchar 256 ID_TABLE

newBrframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newFrameSet calMergeLog, calSynopticMergeLog WSACalib Flag used internally by curation applications tinyint 1 CODE_MISC

newFrameSet dxsJKmergeLog, dxsMergeLog, gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog, lasMergeLog, lasYJHKmergeLog, udsMergeLog WSA Flag used internally by curation applications tinyint 1 CODE_MISC

newH2frame calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newH2frame gpsJHKmergeLog, gpsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newHframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newHframe dxsJKmergeLog, dxsMergeLog, gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog, lasMergeLog, lasYJHKmergeLog, udsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJ_1frame lasMergeLog, lasYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJ_2frame lasMergeLog, lasYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJframe dxsJKmergeLog, dxsMergeLog, gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog, udsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newK_1frame gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newK_2frame gcsMergeLog, gcsZYJHKmergeLog, gpsJHKmergeLog, gpsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newKframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newKframe dxsJKmergeLog, dxsMergeLog, lasMergeLog, lasYJHKmergeLog, udsMergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newlyIngested Multiframe WSA Curation flag for internal use only (0=no, 1=yes) tinyint 1 1 ??

newlyIngested Multiframe WSACalib Curation flag for internal use only (0=no, 1=yes) tinyint 1 1 ??

newlyIngested Multiframe WSATransit Curation flag for internal use only (0=no, 1=yes) tinyint 1 1 ??

newNbjframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newYframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newYframe gcsMergeLog, gcsZYJHKmergeLog, lasMergeLog, lasYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newZframe calMergeLog, calSynopticMergeLog WSACalib new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newZframe gcsMergeLog, gcsZYJHKmergeLog WSA new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

nFlag rosat_bsc, rosat_fsc ROSAT nearby sources affecting SASS flux determination varchar 1 CODE_MISC

nFoc Multiframe WSA Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2 -9999 NUMBER

nFoc Multiframe WSACalib Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2 -9999 NUMBER

nFoc Multiframe WSATransit Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2 -9999 NUMBER

nFocScan Multiframe WSA Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2 -9999 NUMBER

nFocScan Multiframe WSACalib Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2 -9999 NUMBER

nFocScan Multiframe WSATransit Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2 -9999 NUMBER

nFrames calVariability WSACalib Number of frames with good detections used to calculate astrometric fits int 4 0 NUMBER

The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.

nFrames dxsVariability, udsVariability WSA Number of frames with good detections used to calculate astrometric fits int 4 0 NUMBER

The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.

nFrames gcsPointSource, gcsSource, gcsZYJHKsource, gpsJHKsource, gpsPointSource, gpsSource, lasExtendedSource, lasPointSource, lasSource, lasYJHKsource, reliableGcsPointSource, reliableGpsPointSource, reliableLasPointSource WSA No. of frames used for this proper motion measurement tinyint 1 0 NUMBER

nhcon iras_psc IRAS Number of times observed (<25) tinyint 1 NUMBER

nId iras_psc IRAS Number of positional associations (<25). tinyint 1 NUMBER

night_key twomass_xsc 2MASS key to night data record in "scan DB". smallint 2 ID_NUMBER

nightZPCat MultiframeDetector WSA Average photometric zero point for night {catalogue extension keyword: NIGHTZPT} real 4 mags -0.9999995e9 ??

nightZPCat MultiframeDetector WSACalib Average photometric zero point for night {catalogue extension keyword: NIGHTZPT} real 4 mags -0.9999995e9 ??

nightZPCat MultiframeDetector WSATransit Average photometric zero point for night {catalogue extension keyword: NIGHTZPT} real 4 mags -0.9999995e9 ??

nightZPCat PreviousMFDZP WSA Average photometric zero point for night real 4 mags -0.9999995e9 ??

nightZPCat PreviousMFDZP WSACalib Average photometric zero point for night real 4 mags -0.9999995e9 ??

nightZPErrCat MultiframeDetector WSA Photometric zero point sigma for night {catalogue extension keyword: NIGHTZRR}
<0.05 mags for a good night real 4 mags -0.9999995e9 ??

nightZPErrCat MultiframeDetector WSACalib Photometric zero point sigma for night {catalogue extension keyword: NIGHTZRR}
<0.05 mags for a good night real 4 mags -0.9999995e9 ??

nightZPErrCat MultiframeDetector WSATransit Photometric zero point sigma for night {catalogue extension keyword: NIGHTZRR}
<0.05 mags for a good night real 4 mags -0.9999995e9 ??

nightZPErrCat PreviousMFDZP WSA Photometric zero point sigma for night
<0.05 mags for a good night real 4 mags -0.9999995e9 ??

nightZPErrCat PreviousMFDZP WSACalib Photometric zero point sigma for night
<0.05 mags for a good night real 4 mags -0.9999995e9 ??

nightZPNum MultiframeDetector WSA Number of ZP in band used to calculate nightZPCat {catalogue extension keyword: NIGHTNUM} int 4 mags -99999999 ??

nightZPNum MultiframeDetector WSACalib Number of ZP in band used to calculate nightZPCat {catalogue extension keyword: NIGHTNUM} int 4 mags -99999999 ??

nightZPNum MultiframeDetector WSATransit Number of ZP in band used to calculate nightZPCat {catalogue extension keyword: NIGHTNUM} int 4 mags -99999999 ??

nightZPNum PreviousMFDZP WSA Number of ZP in band used to calculate nightZPCat int 4 mags -99999999 ??

nightZPNum PreviousMFDZP WSACalib Number of ZP in band used to calculate nightZPCat int 4 mags -99999999 ??

njitter Multiframe WSA Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2 -9999 NUMBER

njitter Multiframe WSACalib Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2 -9999 NUMBER

njitter Multiframe WSATransit Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2 -9999 NUMBER

nLrs iras_psc IRAS Number of significant LRS spectra tinyint 1 NUMBER

nopt_mchs twomass_psc 2MASS The number of USNO-A2.0 or Tycho 2 optical sources found within a 5" radius of the TWOMASS position. smallint 2 NUMBER

nPass RequiredFilters WSA the number of passes that will be made smallint 2 NUMBER

nPass RequiredFilters WSACalib the number of passes that will be made smallint 2 NUMBER

nPass RequiredFilters WSATransit the number of passes that will be made smallint 2 NUMBER

nPixels RequiredMosaic WSACalib CASU/SEX source extraction tool option for minimum number of connected pixels in a detected source (recommended value=4) smallint 2 -9999 ??

nPixels RequiredMosaic WSATransit CASU/SEX source extraction tool option for minimum number of connected pixels in a detected source (recommended value=4) smallint 2 -9999 ??

nPixels RequiredMosaic, RequiredStack WSA CASU/SEX source extraction tool option for minimum number of connected pixels in a detected source (recommended value=4) smallint 2 -9999 ??

numAxes MultiframeDetector WSA Number of data axes; eg. 2 tinyint 1 NUMBER

numAxes MultiframeDetector WSACalib Number of data axes; eg. 2 tinyint 1 NUMBER

numAxes MultiframeDetector WSATransit Number of data axes; eg. 2 tinyint 1 NUMBER

numberStk RequiredStack WSA Number of intermediate stacks. If default, stack all good quality stacks int 4 -99999999

numberStk RequiredStack WSACalib Number of intermediate stacks. If default, stack all good quality stacks int 4 -99999999

numberStk RequiredStack WSATransit Number of intermediate stacks. If default, stack all good quality stacks int 4 -99999999

numDetectors Multiframe WSA The number of "detectors" (=image extensions in FITS file) tinyint 1 ??

numDetectors Multiframe WSACalib The number of "detectors" (=image extensions in FITS file) tinyint 1 ??

numDetectors Multiframe WSATransit The number of "detectors" (=image extensions in FITS file) tinyint 1 ??

numExp Multiframe WSA Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2 -9999 NUMBER

numExp Multiframe WSACalib Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2 -9999 NUMBER

numExp Multiframe WSATransit Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2 -9999 NUMBER

numInts Multiframe WSA Number of integrations in observation {image primary HDU keyword: NINT} smallint 2 NUMBER

numInts Multiframe WSACalib Number of integrations in observation {image primary HDU keyword: NINT} smallint 2 NUMBER

numInts Multiframe WSATransit Number of integrations in observation {image primary HDU keyword: NINT} smallint 2 NUMBER

numReads Multiframe WSA Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2 -9999 NUMBER

numReads Multiframe WSACalib Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2 -9999 NUMBER

numReads Multiframe WSATransit Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2 -9999 NUMBER

numRms CurrentAstrometry WSACalib No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4 -99999999 FIT_PARAM_VALUE

numRms CurrentAstrometry WSATransit No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4 -99999999 FIT_PARAM_VALUE

numRms CurrentAstrometry, PreviousAstrometry WSA No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4 -99999999 FIT_PARAM_VALUE

numZPCat MultiframeDetector WSA Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword: NUMZPT} int 4 -99999999

numZPCat MultiframeDetector WSACalib Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword: NUMZPT} int 4 -99999999

numZPCat MultiframeDetector WSATransit Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword: NUMZPT} int 4 -99999999

numZPCat PreviousMFDZP WSA Number of standards used in determining photZP and photZPErr int 4 -99999999

numZPCat PreviousMFDZP WSACalib Number of standards used in determining photZP and photZPErr int 4 -99999999

nuStep Multiframe WSA Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2 -9999 NUMBER

nuStep Multiframe WSACalib Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2 -9999 NUMBER

nuStep Multiframe WSATransit Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2 -9999 NUMBER

NVSS nvssSource NVSS Source name varchar 14 ID_MAIN

WFAU, Institute for Astronomy,
Royal Observatory, Blackford Hill
Edinburgh, EH9 3HJ, UK
Tel +44 131 668 8356 (office)
or +44 131 668 8100 (switchboard)

wsa-support@roe.ac.uk
17/02/2010